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Transportation in Social Media: an automatic classifier for travel-related tweets [article]

João Pereira, Arian Pasquali, Pedro Saleiro, Rosaldo Rossetti
2017 arXiv   pre-print
In this work we focus on exploring geo-located tweets in order to create a travel-related tweet classifier using a combination of bag-of-words and word embeddings.  ...  In the last years researchers in the field of intelligent transportation systems have made several efforts to extract valuable information from social media streams.  ...  The main goal of this work lies upon the development of an automatic system capable of discriminating travel-related tweets from a stream of geo-located tweets.  ... 
arXiv:1706.05090v1 fatcat:3edvddevlbeivlqgs4osf2d5jy

Transportation in Social Media: An Automatic Classifier for Travel-Related Tweets [chapter]

João Pereira, Arian Pasquali, Pedro Saleiro, Rosaldo Rossetti
2017 Lecture Notes in Computer Science  
In this work we focus on exploring geolocated tweets in order to create a travel-related tweet classifier using a combination of bag-of-words and word embeddings.  ...  In the last years researchers in the field of intelligent transportation systems have made several efforts to extract valuable information from social media streams.  ...  The main goal of this work lies upon the development of an automatic system capable of discriminating travel-related tweets from a stream of geo-located tweets.  ... 
doi:10.1007/978-3-319-65340-2_30 fatcat:64av2zkbr5dkbaebnm7sizvdcy

Mining Social Media for Open Innovation in Transportation Systems [article]

Daniela Ulloa, Pedro Saleiro, Rosaldo J. F. Rossetti, Elis Regina Silva
2016 arXiv   pre-print
This work proposes a novel framework for the development of new products and services in transportation through an open innovation approach based on automatic content analysis of social media data.  ...  While there is no change in the image of Uber, a large increase in the number of tweets mentioning the company is observed, which meant a free and important diffusion of its product.  ...  development of new products and services in transportation using an open innovation approach, based on automatic content analysis of social media data.  ... 
arXiv:1610.09894v1 fatcat:aeqghnncprgpxh3zqfcbacus2i

Spatial Data Mining of Public Transport Incidents reported in Social Media [article]

Kamil Raczycki, Marcin Szymański, Yahor Yeliseyenka, Piotr Szymański, Tomasz Kajdanowicz
2021 arXiv   pre-print
We successfully build an information type classifier for social media posts, detect stop names in posts, and relate them to GPS coordinates, obtaining a spatial understanding of long-term aggregated phenomena  ...  Public transport agencies use social media as an essential tool for communicating mobility incidents to passengers.  ...  Citizen science therefore, heavily relies on the automatic spatial understanding of social media information related to public transport phenomena.  ... 
arXiv:2110.05573v1 fatcat:5y2otvwzi5cpzc7lgr3yjy5hua

Social Media Text Processing and Semantic Analysis for Smart Cities [article]

João Filipe Figueiredo Pereira
2017 arXiv   pre-print
We then use a combination of bag-of-embeddings and traditional bag-of-words to train travel-related classifiers in both Portuguese and English to filter travel-related content from non-related.  ...  With the goal of extracting knowledge from social media streams that might be useful in the context of intelligent transportation systems and smart cities, we designed and developed a framework that provides  ...  To my colleagues, specially, Henrique Ferrolho: thank you for the friendship, patience and support in these five long years.  ... 
arXiv:1709.03406v1 fatcat:styrizf3k5caxoh33xqaonkpye

Incident detection using data from social media

Angelica Salas, Panagiotis Georgakis, Yannis Petalas
2017 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)  
Our approach can detect traffic related tweets with an accuracy of 88.27%.  ...  We present a methodology for retrieving, processing, and classifying public tweets by combining Natural Language Processing (NLP) techniques with a Support Vector Machine algorithm (SVM) for text classification  ...  In recent years, social media has been exploited as a source of real-time data.  ... 
doi:10.1109/itsc.2017.8317967 dblp:conf/itsc/SalasGP17 fatcat:skzgznnigja5xkvlqeiyaosxmq

TensiStrength: Stress and relaxation magnitude detection for social media texts

Mike Thelwall
2017 Information Processing & Management  
The effectiveness of TensiStrength depends on the nature of the tweets classified, with tweets that are rich in stress-related terms being particularly problematic.  ...  This article describes TensiStrength, a system to detect the strength of stress and relaxation expressed in social media text messages.  ...  Within social media, a neural network approach has been used to detect short term or longer term stress in social media for individuals, based upon a range of factors, including the emotions expressed  ... 
doi:10.1016/j.ipm.2016.06.009 fatcat:en56cnp43rh25jyifqwqajdk4i

Opinion Mining on Social Media Transit Tweets using Text Pre-Processing and Machine Learning Techniques

The regional transportation agencies use social media as a tool to provide information to the public and seek their inputs and ideas for meaningful decision making in transportation activities.  ...  Capturing public insights related to transit systems in social media has gained huge popularity presently.  ...  Social Media in transportation tweet assessment [1] Presented a methodology for the automatic extraction of transportation-related information from TripAdvisor. [2] Proposed a deep learning approach  ... 
doi:10.35940/ijitee.a4631.119119 fatcat:35lluyutzzftvbwc3mi4ignpau

Utilising Location Based Social Media in Travel Survey Methods

Alireza Abbasi, Taha Hossein Rashidi, Mojtaba Maghrebi, S. Travis Waller
2015 Proceedings of the 8th ACM SIGSPATIAL International Workshop on Location-Based Social Networks - LBSN'15  
As a result, the capacity of Twitter data in complementing other sources of transport related data such as household travel surveys or traffic count data is examined.  ...  This paper discusses how social media data can be used indirectly and with minimal cost to extract travel attributes such as trip purpose and activity location.  ...  Using Social Media for Travel Detection and Analysis In the literature there are a few studies that have focused on applications of social media and social network services in transportation.  ... 
doi:10.1145/2830657.2830660 dblp:conf/gis/AbbasiRMW15 fatcat:llinf2wygfh7tlydtacc3hjkxq

Automating a framework to extract and analyse transport related social media content: The potential and the challenges

Tsvi Kuflik, Einat Minkov, Silvio Nocera, Susan Grant-Muller, Ayelet Gal-Tzur, Itay Shoor
2017 Transportation Research Part C: Emerging Technologies  
The initial phase in the program of research reported here proposed a framework for mining transport-related information from social media , demonstrated and evaluated it using transport-related tweets  ...  The results presented show a strong degree of success in the identification of transport related tweets, with similar success in identifying tweets that expressed an opinion about transport services.  ...  Mining of Social Media in the Transport Domain There has been a recent surge of initiatives concerning the use of SM UGC for transport-related purposes.  ... 
doi:10.1016/j.trc.2017.02.003 fatcat:vovlrmfmbbhd3cjvt3xdcvsghe

Arabic Event Detection in Social Media [chapter]

Nasser Alsaedi, Pete Burnap
2015 Lecture Notes in Computer Science  
To the best of our knowledge, this study is the first effort to identify real-world events in Arabic from social media.  ...  One such source of online information is social media. Twitter, as a form of social media, is a popular micro-blogging web application serving hundreds of millions of users.  ...  For classification, three human annotators manually labeled 1200 tweets in to two classes "Event" and "Non-Event" to train our classifiers (500 Non-Event tweets and 700 Event-related tweets).  ... 
doi:10.1007/978-3-319-18111-0_29 fatcat:wrmfs7expbdsbljqt5uwgsqqvm

From Twitter to Traffic Predictor: Next-Day Morning Traffic Prediction Using Social Media Data [article]

Weiran Yao, Sean Qian
2020 arXiv   pre-print
The occurrence of big events in the evening before, represented by higher or lower tweet sentiment than normal, often implies lower travel demand in the next morning than normal days.  ...  We find that, in general, the earlier people rest as indicated from Tweets, the more congested roads will be in the next morning.  ...  Center for mobility 795 sponsored by the U.S.  ... 
arXiv:2009.13794v1 fatcat:l52fq6iqbfaqnnjzn7a4rxuscq

TravelBot: Utilising social media dialogue to provide journey disruption alerts

Paul Gault, Caitlin D. Cottrill, David Corsar, Peter Edwards, John D. Nelson, Milan Markovic, Mujtaba Mehdi, Somayajulu Sripada
2019 Transportation Research Interdisciplinary Perspectives  
The Tweeting Travel study developed an understanding of the types of dialogues that can unfold on social media between passengers and a simulated travel advice system and then used this to shape development  ...  Use of social media in the public transport sector is rapidly increasing, driven by both passenger demand, and recognition by transport operators of the insights that social media enables.  ...  We extend our grateful thanks to the participants who have contributed to the studies throughout, and to the industry partner FirstGroup plc for their support.  ... 
doi:10.1016/j.trip.2019.100062 fatcat:aknb65wxbfeftdryq5jtzdbw5e

Empowering Real-Time Traffic Reporting Systems With NLP-Processed Social Media Data

Xiangpeng Wan, Michael C. Lucic, Hakim Ghazzai, Yehia Massoud
2020 IEEE Open Journal of Intelligent Transportation Systems  
In this paper, we develop an automated Natural Language Processing (NLP)-based framework to empower and complement traffic reporting solutions by text mining social media, extracting desired information  ...  Despite their abundance, the use of social media data in ITS has gained more and more attention as of now.  ...  Applying Natural Language Processing (NLP) in social media for the purpose of leveraging underutilized transportation-related posts for ITS applications is an active area in research.  ... 
doi:10.1109/ojits.2020.3024245 fatcat:ozfckwdpurc7xb4csch532ntjy

Detection of Damage and Failure Events of Road Infrastructure Using Social Media [chapter]

Aibek Musaev, Zhe Jiang, Steven Jones, Pezhman Sheinidashtegol, Mirbek Dzhumaliev
2018 Lecture Notes in Computer Science  
Instead, we propose to use social sensor big data to detect and estimate these issues based on the public's activity. As a demonstration, we generate a map of detected road problems based on tweets.  ...  Finally, we analyze the most influential users using an extension of PageRank.  ...  Information derived from social media has been shown to be useful in understanding travel patterns [30] .  ... 
doi:10.1007/978-3-319-94289-6_9 fatcat:osei76hafvfkbhcxr2illmln7a
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